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Haibo Chu, Zhuoqi Wang and Chong Nie
Accurate and reliable monthly streamflow prediction plays a crucial role in the scientific allocation and efficient utilization of water resources. In this paper, we proposed a prediction framework that integrates the input variable selection method and ...
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Ekaterini Hadjisolomou, Maria Rousou, Konstantinos Antoniadis, Lavrentios Vasiliades, Ioannis Kyriakides, Herodotos Herodotou and Michalis Michaelides
Eutrophication is a major environmental issue with many negative consequences, such as hypoxia and harmful cyanotoxin production. Monitoring coastal eutrophication is crucial, especially for island countries like the Republic of Cyprus, which are economi...
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Zhenjiang Wu, Chuiyu Lu, Qingyan Sun, Wen Lu, Xin He, Tao Qin, Lingjia Yan and Chu Wu
In recent years, the groundwater level (GWL) and its dynamic changes in the Hebei Plain have gained increasing interest. The GWL serves as a crucial indicator of the health of groundwater resources, and accurately predicting the GWL is vital to prevent i...
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Higuatzi Moreno and Alexander Schaum
Batteries are complex systems involving spatially distributed microscopic mechanisms on different time scales whose adequate interplay is essential to ensure a desired functioning. Describing these phenomena yields nonlinearly coupled partial differentia...
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Mauricio Herrera and Alex Godoy-Faúndez
The COVID-19 crisis has shown that we can only prevent the risk of mass contagion through timely, large-scale, coordinated, and decisive actions. This pandemic has also highlighted the critical importance of generating rigorous evidence for decision-maki...
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Dmitry Pavlyuk
Transfer learning is a modern concept that focuses on the application of ideas, models, and algorithms, developed in one applied area, for solving a similar problem in another area. In this paper, we identify links between methodologies in two fields: vi...
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Jiawei Xie, Jinsong Huang, Cheng Zeng, Shui-Hua Jiang and Nathan Podlich
Conventional planning of maintenance and renewal work for railway track is based on heuristics and simple scheduling. The railway industry is now collecting a large amount of data with the fast-paced development of sensor technologies. These data sets ca...
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Mustafa Al-Mukhtar and Fuaad Al-Yaseen
Total dissolved solids (TDS) and electrical conductivity (EC) are important parameters in determining water quality for drinking and agricultural water, since they are directly associated to the concentration of salt in water and, hence, high values of t...
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Sabrina De Nardi, Claudio Carnevale, Sara Raccagni and Lucia Sangiorgi
Models are a core element in performing local estimation of the climate change input. In this work, a novel approach to perform a fast downscaling of global temperature anomalies on a regional level is presented. The approach is based on a set of data-dr...
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Shiva Gopal Shrestha and Soni M. Pradhanang
The general practice of rainfall-runoff model development towards physically based and spatially explicit representations of hydrological processes is data-intensive and computationally expensive. Physically based models such as the Soil Water Assessment...
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Die Zhang, Yong Ge, Xilin Wu, Haiyan Liu, Wenbin Zhang and Shengjie Lai
Data-driven approaches predict infectious disease dynamics by considering various factors that influence severity and transmission rates. However, these factors may not fully capture the dynamic nature of disease transmission, limiting prediction accurac...
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Lili Jiang and Vicenç Torra
Anonymization and data masking have effects on data-driven models. Different anonymization methods have been developed to provide a good trade-off between privacy guarantees and data utility. Nevertheless, the effects of data protection (e.g., data micro...
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Daniel Clemente, Paulo Rosa-Santos and Francisco Taveira-Pinto
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Kurt R. Lamm, Justin D. Delorit, Michael N. Grussing and Steven J. Schuldt
Organizations with large facility and infrastructure portfolios have used asset management databases for over ten years to collect and standardize asset condition data. Decision makers use these data to predict asset degradation and expected service life...
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Mohammad Najafzadeh and Giuseppe Oliveto
Offshore pipelines are occasionally exposed to scouring processes; detrimental impacts on their safety are inevitable. The process of scouring propagation around offshore pipelines is naturally complex and is mainly due to currents and/or waves. There is...
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Chayut Ngamkhanong, Suraparb Keawsawasvong, Thira Jearsiripongkul, Lowell Tan Cabangon, Meghdad Payan, Kongtawan Sangjinda, Rungkhun Banyong and Chanachai Thongchom
In this paper, Artificial Neural Networks (ANN) have been utilized to predict the stability of a planar tunnel heading in rock mass based on the well-defined Hoek-Brown (HB) yield criterion. The HB model was developed to capture the failure criterion of ...
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José Felix Zapata Usandivaras, Annafederica Urbano, Michael Bauerheim and Bénédicte Cuenot
Improving the predictive capabilities of reduced-order models for the design of injector and chamber elements of rocket engines could greatly improve the quality of early rocket chamber designs. In the present work, we propose an innovative methodology t...
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Yanjun Chen, Shengye Wang and Wei Liu
Over the past years, there has been innovative ideas about data-driven turbulence modeling proposed by scholars all over the world. This paper is a continuity of these significant efforts, with the aim of offering a better representation for turbulence p...
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Manuel Lopez-Martin, Antonio Sanchez-Esguevillas, Luis Hernandez-Callejo, Juan Ignacio Arribas and Belen Carro
This work brings together and applies a large representation of the most novel forecasting techniques, with origins and applications in other fields, to the short-term electric load forecasting problem. We present a comparison study between different cla...
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Péter Koltai, Hao Wu, Frank Noé and Christof Schütte
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